Update app.py

app.py

@@ -1,23 +1,23 @@
-import pandas as pd
-import gradio as gr
-from SmartSearchEngine import search_courses
-
-# Load the DataFrame with embeddings
-df = pd.read_pickle('output/courses_with_embeddings.pkl')
-
-# Define the search function to be used in the Gradio interface
-def gradio_search(query):
-    results = search_courses(query, top_n=5)
-    return results.to_dict(orient='records')
-
-# Create a Gradio interface
-iface = gr.Interface(
-    fn=gradio_search,
-    inputs=gr.Textbox(lines=2, placeholder="Enter your search query here..."),
-    outputs=gr.JSON(label="Search Results"),
-    title="Smart Course Search Tool",
-    description="Search for the most relevant courses on Analytics Vidhya"
-)
-
-# Launch the Gradio interface
+import pandas as pd
+import gradio as gr
+from ./Search Engine/SmartSearchEngine import search_courses
+
+# Load the DataFrame with embeddings
+df = pd.read_pickle('output/courses_with_embeddings.pkl')
+
+# Define the search function to be used in the Gradio interface
+def gradio_search(query):
+    results = search_courses(query, top_n=5)
+    return results.to_dict(orient='records')
+
+# Create a Gradio interface
+iface = gr.Interface(
+    fn=gradio_search,
+    inputs=gr.Textbox(lines=2, placeholder="Enter your search query here..."),
+    outputs=gr.JSON(label="Search Results"),
+    title="Smart Course Search Tool",
+    description="Search for the most relevant courses on Analytics Vidhya"
+)
+
+# Launch the Gradio interface
 iface.launch(share=True)